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Book Review: Learning TensorFlow

Deep Neural Networks (DNNs), upon which deep learning is based, are trained with large amounts of data, and can solve complex tasks with unprecedented accuracy. TensorFlow is a leading open source software framework that helps you build and train neural networks. Here’s a nice resource to help you kick-start your use of TensorFlow – “Learning TensorFlow” by Tom Hope, Yehezkel S. Resheff and Itay Leider.

Large Scale Deep Learning with TensorFlow

In this video presentation from the Spark Summit 2016 conference in San Francisco, Google’s Jeff Dean examines large scale deep learning with the TensorFlow framework. Jeff joined Google in 1999 and is currently a Google Senior Fellow.

TensorFlow Tutorial – Simple Linear Model

In this excellent tutorial video presentation below, Magnus Erik Hvass Pedersen demonstrates the basic workflow of using TensorFlow with a simple linear model. You should be familiar with basic linear algebra, Python and the Jupyter Notebook editor. It also helps if you have a basic understanding of Machine Learning and classification.

Performance Optimization of Deep Learning Frameworks on Modern Intel Architectures

In this video from the Intel HPC Developer Conference, Elmoustapha Ould-ahmed-vall from Intel describes how the company is doubling down to optimize Machine Learning frameworks for Intel Platforms. Using open source frameworks as a starting point, surprising speedups are possible using Intel technologies.

Large-Scale Deep Learning with TensorFlow

We bring you the keynote presentation below from the recent Spark Summit 2016 held in San Francisco on June 6-8. Speaker Jeff Dean joined Google in 1999 and is currently a Google Senior Fellow.